U.S. patent application number 11/388766 was filed with the patent office on 2007-09-27 for method for predicting liver fibrosis and related pathologies.
This patent application is currently assigned to The University of Western Australia. Invention is credited to Leon Adams, Mahesh Bulsara, Gary Jeffrey, Enrico Rossi.
Application Number | 20070225919 11/388766 |
Document ID | / |
Family ID | 38534608 |
Filed Date | 2007-09-27 |
United States Patent
Application |
20070225919 |
Kind Code |
A1 |
Jeffrey; Gary ; et
al. |
September 27, 2007 |
Method for predicting liver fibrosis and related pathologies
Abstract
Provided herein are methods of detecting and staging liver
fibrosis in an individual with liver disease. Also provided are
methods of detecting necroinflammatory activity. Invention methods
utilize four serum markers, age, and gender to determine an end
value. The end value is compared to a cut-off value, in order to
identify significant fibrosis (METAVIR stages F2 to F4), or an
absence of advanced fibrosis (stages F3 and F4) or cirrhosis (stage
F4). In particular aspects, progression or treatment of liver
fibrosis can be monitored by invention methods. The end value is
also used to distinguish between no to mild necroinflammatory
activity (METAVIR grade A0 to A1) and moderate to severe
necroinflammatory activity (grade A2 to A3).
Inventors: |
Jeffrey; Gary; (Perth,
AU) ; Rossi; Enrico; (Nedlands, AU) ; Bulsara;
Mahesh; (Bull Creek, AU) ; Adams; Leon;
(Attadale, AU) |
Correspondence
Address: |
Richard J. Warburg;FOLEY & LARDNER LLP
P.O. Box 80278
San Diego
CA
92138-0278
US
|
Assignee: |
The University of Western
Australia
|
Family ID: |
38534608 |
Appl. No.: |
11/388766 |
Filed: |
March 24, 2006 |
Current U.S.
Class: |
702/19 |
Current CPC
Class: |
G01N 2400/40 20130101;
G01N 33/728 20130101; G01N 33/66 20130101; G01N 2800/085 20130101;
C12Q 1/48 20130101; G01N 33/6893 20130101 |
Class at
Publication: |
702/019 |
International
Class: |
G06F 19/00 20060101
G06F019/00 |
Claims
1. A method of diagnosing liver fibrosis in a patient, said method
comprising: a) assaying the concentration of markers in a sample
from said patient, wherein said markers are .alpha.2-macroglobulin,
.gamma.-glutamyl transferase (GGT), bilirubin, and hyaluronic acid;
b) determining an end value, H, using an algorithm, wherein said
algorithm is, H=y/(1+y) wherein, y=exp
(-X-(C.sub.1*age)+(C.sub.2*gender)+(C.sub.3*.alpha.2-macroglobulin)+(C.su-
b.4*hyaluronic acid)+(C.sub.5*bilirubin)-(C.sub.6*GGT)) wherein, X
is between -6.8460 and -1.5257 inclusive, C.sub.1 is between
-0.0877 and 0.0378 inclusive, C.sub.2 is between 0.3064 and 1.7992
inclusive, C.sub.3 is between 0.4406 and 1.5672 inclusive, C.sub.4
is between 0.0090 and 0.0515 inclusive, C.sub.5 is between -0.0099
and 0.1482 inclusive, C.sub.6 is between -0.0055 and 0.0032
inclusive, and wherein, age is in years, male gender=1, female
gender=0, .alpha..sub.2-macroglobulin is in g/L, hyaluronic acid is
in .mu.g/L, bilirubin is in .mu.mol/L, GGT is in U/L; and c)
comparing said end value, H, to a cut-off value that is predictive
of a disease or symptom in order to determine the presence of liver
fibrosis in said patient.
2. A method according to claim 1, wherein y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha..sub.2-macroglobul-
in)+(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT)).
3. A method according to claim 1, wherein said cut-off value is
about 0.5, and wherein an end value, H, of greater than or equal to
about 0.5 is indicative of significant fibrosis or an end value, H,
of less than about 0.5 is indicative of the absence of advanced
fibrosis.
4. A method according to claim 1, wherein said cut-off value is
about 0.84 and an end value, H, less than about 0.84 is indicative
of the absence of cirrhosis of the liver.
5. A method according to claim 1, wherein said cut-off value is
about 0.84 and an end value, H, greater than or equal to about 0.84
is indicative the presence of cirrhosis.
6. A method according to claim 1, wherein said sample is serum.
7. A method according to claim 1, wherein said sample is
plasma.
8. The method of claim 1, wherein said end value is used for the
choice of a suitable treatment for the patient.
9. The method of claim 1, wherein said patient suffers from a
disease involving liver fibrosis.
10. The method of claim 9, wherein said disease is selected from
the group consisting of: hepatitis B, hepatitis C, alcoholism and
alcohol abuse, alcoholic liver disease, hemochromatosis, metabolic
disease, diabetes, obesity, nonalcoholic fatty liver disease,
alcoholic fatty liver, autoimmune hepatitis, primary biliary
cirrhosis, primary sclerosing cholangitis, .alpha.1-antitrypsin
deficit, Wilson disease, chronic rejection following liver
transplantation, and recurrent liver disease following liver
transplantation.
11. The method of claim 10, wherein said disease is hepatitis
C.
12. The method of claim 10, wherein said disease is nonalcoholic
fatty liver disease.
13. The method of claim 10, wherein said disease is alcoholic fatty
liver.
14. A method of monitoring progression of liver fibrosis in a
patient, said method comprising: a) obtaining a first sample from
said patient; b) assaying the concentration of markers in a sample
said patient, wherein said markers are .alpha.2-macroglobulin,
.gamma.-glutamyl transferase (GGT), bilirubin, and hyaluronic acid;
c) determining an end value, H, using an algorithm, wherein said
algorithm is, H=y/(1+y) wherein, y=exp
(-X-(C.sub.1*age)+(C.sub.2*gender)+(C.sub.3*.alpha.2-macroglobulin)+(C.su-
b.4*hyaluronic acid)+(C.sub.5*bilirubin)-(C.sub.6*GGT)) wherein, X
is between -6.8460 and -1.5257 inclusive, C.sub.1 is between
-0.0877 and 0.0378 inclusive, C.sub.2 is between 0.3064 and 1.7992
inclusive, C.sub.3 is between 0.4406 and 1.5672 inclusive, C.sub.4
is between 0.0090 and 0.0515 inclusive, C.sub.5 is between -0.0099
and 0.1482 inclusive, C.sub.6 is between -0.0055 and 0.0032
inclusive, and wherein, age is in years, male gender=1, female
gender=0, .alpha..sub.2-macroglobulin is in g/L, hyaluronic acid is
in .mu.g/L, bilirubin is in .mu.mol/L, GGT is in U/L; and d)
comparing said end value, H, to a cut-off value that is predictive
of a disease or symptom to determine the extent of liver fibrosis
in said patient; e) obtaining a second sample from said patient,
wherein said second sample is obtained after said first sample; f)
repeating steps b)-d) to determine the extent of liver fibrosis as
indicated by said second sample; and g) comparing the extent of
liver fibrosis indicated by said first sample to the extent of
liver fibrosis indicated by said second sample; wherein a higher
extent in liver fibrosis as indicated by the second sample in
comparison to the first sample indicates progression in liver
fibrosis or a lesser extent in liver fibrosis as indicated by the
second sample in comparison to the first sample indicates a
regression in liver fibrosis.
15. A method according to claim 14, wherein y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha..sub.2-macroglobul-
in)+(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT)).
16. A method according to claim 14, wherein said cut-off value is
0.5, and wherein an end value, H, of greater than or equal to said
cut-off value is indicative of significant fibrosis or an end
value, H, of less than said cut-off value is indicative of the
absence of advanced fibrosis.
17. A method according to claim 14, wherein said cut-off value is
about 0.84 and an end value, H, of less than about 0.84 is
indicative of an absence of cirrhosis of the liver.
18. A method according to claim 14, wherein said cut-off value is
about 0.84 and an end value, H, greater than or equal to about 0.84
is indicative of the presence of cirrhosis of the liver.
19. A method according to claim 14, wherein said sample is
serum.
20. A method according to claim 14, wherein said sample is
plasma.
21. The method of claim 14, wherein said patient suffers from a
disease involving liver fibrosis.
22. The method of claim 21, wherein said disease is selected from
the group consisting of: hepatitis B, hepatitis C, alcoholism and
alcohol abuse, alcoholic liver disease, hemochromatosis, metabolic
disease, diabetes, obesity, nonalcoholic fatty liver disease,
alcoholic fatty liver, autoimmune hepatitis, primary biliary
cirrhosis, primary sclerosing cholangitis, .alpha.1-antitrypsin
deficit, Wilson disease, chronic rejection following liver
transplantation, and recurrent liver disease following liver
transplantation.
23. The method of claim 22, wherein said disease is hepatitis
C.
24. The method of claim 22, wherein said disease is nonalcoholic
fatty liver disease.
25. The method of claim 22, wherein said disease is alcoholic fatty
liver.
26. A method of monitoring the efficacy of liver fibrosis therapy
in a patient in need thereof, said method comprising: a) obtaining
a first sample from said patient; b) assaying the concentration of
markers in a sample from said patient, wherein said markers are
.alpha.2-macroglobulin, .gamma.-glutamyl transferase (GGT),
bilirubin, and hyaluronic acid; c) determining an end value, H,
using an algorithm, wherein said algorithm is, H=y/(1+y) wherein,
y=exp(-X-(C.sub.1*age)+(C.sub.2*gender)+(C.sub.3*.alpha.2-macroglobulin)+-
(C.sub.4*hyaluronic acid)+(C.sub.5*bilirubin)-(C.sub.6*GGT))
wherein, X is between -6.8460 and -1.5257 inclusive, C.sub.1 is
between -0.0877 and 0.0378 inclusive, C.sub.2 is between 0.3064 and
1.7992 inclusive, C.sub.3 is between 0.4406 and 1.5672 inclusive,
C.sub.4 is between 0.0090 and 0.0515 inclusive, C.sub.5 is between
-0.0099 and 0.1482 inclusive, C.sub.6 is between -0.0055 and 0.0032
inclusive, and wherein, age is in years, male gender=1, female
gender=0, .alpha..sub.2-macroglobulin is in g/L, hyaluronic acid is
in .mu.g/L, bilirubin is in .mu.mol/L, GGT is in U/L; and d)
comparing said end value, H, to a cut-off value that is predictive
of a disease or symptom to determine the extent of liver fibrosis
in said patient; e) obtaining a second sample from said patient,
wherein said second sample is obtained after said first sample; f)
repeating steps b)-d) to determine the extent of liver fibrosis as
indicated by said second sample; and g) comparing the extent of
liver fibrosis indicated by said first sample to the extent of
liver fibrosis indicated by said second sample; wherein an
equivalent or higher extent in liver fibrosis as indicated by the
second sample in comparison to the first sample indicates the liver
fibrosis therapy is not efficacious in treating liver fibrosis, or
a lesser extent in liver fibrosis as indicated by the second sample
in comparison to the first sample indicates the liver fibrosis
therapy is efficacious in treating liver fibrosis.
27. A method according to claim 26, wherein y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha..sub.2-macroglobul-
in)+(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT)).
28. A method according to claim 26, wherein said cut-off value is
0.5, and wherein an end value, H, of greater than or equal to said
cut-off value is indicative of significant fibrosis or an end
value, H, of less than said cut-off value is indicative of the
absence of advanced fibrosis.
29. A method according to claim 26, wherein said cut-off value is
about 0.84 and an end value, H, of less than about 0.84 is
indicative of an absence of cirrhosis of the liver.
30. A method according to claim 26, wherein said cut-off value is
about 0.84 and an end value, H, greater than or equal to about 0.84
is indicative of the presence of cirrhosis of the liver.
31. A method according to claim 26, wherein said sample is
serum.
32. A method according to claim 26, wherein said sample is
plasma.
33. The method of claim 26, wherein said patient suffers from a
disease involving liver fibrosis.
34. The method of claim 33, wherein said disease is selected from
the group consisting of: hepatitis B, hepatitis C, alcoholism and
alcohol abuse, alcoholic liver disease, hemochromatosis, metabolic
disease, diabetes, obesity, nonalcoholic fatty liver disease,
alcoholic fatty liver, autoimmune hepatitis, primary biliary
cirrhosis, primary sclerosing cholangitis, .alpha.1-antitrypsin
deficit, Wilson disease, chronic rejection following liver
transplantation, and recurrent liver following liver
transplantation.
35. The method of claim 34, wherein said disease is hepatitis
C.
36. The method of claim 34, wherein said disease is nonalcoholic
fatty liver disease.
37. The method of claim 34, wherein said disease is alcoholic fatty
liver.
38. A method of diagnosing hepatic necroinflammatory activity in a
patient, said method comprising: a) assaying the concentration of
markers in a sample from said patient, wherein said markers are
.alpha.2-macroglobulin, .gamma.-glutamyl transferase (GGT),
bilirubin, and hyaluronic acid; b) determining an end value, H,
using an algorithm, wherein said algorithm is, H=y/(1+y) wherein,
y=exp
(-X-(C.sub.1*age)+(C.sub.2*gender)+(C.sub.3*.alpha.2-macroglobulin)+(C.su-
b.4*hyaluronic acid)+(C.sub.5*bilirubin)-(C.sub.6*GGT)) wherein, X
is between -6.8460 and -1.5257 inclusive, C.sub.1 is between
-0.0877 and 0.0378 inclusive, C.sub.2 is between 0.3064 and 1.7992
inclusive, C.sub.3 is between 0.4406 and 1.5672 inclusive, C.sub.4
is between 0.0090 and 0.0515 inclusive, C.sub.5 is between -0.0099
and 0.1482 inclusive, C.sub.6 is between -0.0055 and 0.0032
inclusive, and wherein, age is in years, male gender=1, female
gender=0, .alpha..sub.2-macroglobulin is in g/L, hyaluronic acid is
in .mu.g/L, bilirubin is in .mu.mol/L, GGT is in U/L; and c)
comparing said end value, H, to a cut-off value that is predictive
of a disease or symptom in order to determine the presence of
necroinflammatory activity in said patient.
39. A method according to claim 38, wherein y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha..sub.2-macroglobul-
in)+(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT)).
40. A method according to claim 38, wherein said cut-off value is
0.5, and wherein an end value, H, of greater than or equal to said
cut-off value is indicative of moderate/severe necroinflammatory
activity or an end value, H, of less than said cut-off value is
indicative of the no/mild necroinflammatory activity.
41. A method according to claim 38, wherein said sample is
serum.
42. A method according to claim 38, wherein said sample is
plasma.
43. The method of claim 38, wherein said patient suffers from a
disease involving liver fibrosis.
44. The method of claim 43, wherein said patient suffers from a
disease selected from the group consisting of: hepatitis B,
hepatitis C, alcoholism and alcohol abuse, alcoholic liver disease,
hemochromatosis, metabolic disease, diabetes, obesity, nonalcoholic
fatty liver disease, alcoholic fatty liver, autoimmune hepatitis,
primary biliary cirrhosis, primary sclerosing cholangitis,
.alpha.1-antitrypsin deficit, Wilson disease, chronic rejection
following liver transplantation, and recurrent liver disease
following liver transplantation.
45. The method of claim 44, wherein said disease is hepatitis
C.
46. The method of claim 44, wherein said disease is nonalcoholic
fatty liver disease.
47. The method of claim 44, wherein said disease is alcoholic fatty
liver.
48. A system for diagnosing the presence of liver fibrosis in an
individual, said system comprising, an input device for entry of
data comprising .alpha..sub.2-macroglobulin, hyaluronic acid,
bilirubin, and .gamma.-glutamyl transferase levels as determined
from a sample from said individual and data for age and gender, a
processor connected to said input device, said processor having
software for 1) computing an end value, H, using an algorithm,
wherein said algorithm is, H=y/(1+y) wherein, y=exp
(-X-(C.sub.1*age)+(C.sub.2*gender)+(C.sub.3*.alpha.2-macroglobulin)+(C.su-
b.4*hyaluronic acid)+(C.sub.5*bilirubin)-(C.sub.6*GGT)) wherein, X
is between -6.8460 and -1.5257 inclusive, C.sub.1 is between
-0.0877 and 0.0378 inclusive, C.sub.2 is between 0.3064 and 1.7992
inclusive, C.sub.3 is between 0.4406 and 1.5672 inclusive, C.sub.4
is between 0.0090 and 0.0515 inclusive, C.sub.5 is between -0.0099
and 0.1482 inclusive, C.sub.6 is between -0.0055 and 0.0032
inclusive, and wherein, age is in years, male gender=1, female
gender=0, .alpha..sub.2-macroglobulin is in g/L, hyaluronic acid is
in .mu.g/L, bilirubin is in .mu.mol/L, GGT is in U/L; and 2)
comparing said end value to a cut-off value that is predictive of a
disease or symptom to diagnose the presence of liver fibrosis, a
data output device for receiving said diagnosis, connected to said
processor.
49. A method according to claim 48, wherein y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha..sub.2-macroglobul-
in)+(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT)).
50. A system of claim 48, wherein said cut-off value is 0.5, and
wherein an end value, H, of greater than or equal to said cut-off
value is indicative of significant fibrosis or an end value, H, of
less than said cut-off value is indicative of the absence of
advanced fibrosis.
51. The system of claim 48, wherein said cut-off value is about
0.84 and an end value, H, of less than about 0.84 is indicative of
an absence of cirrhosis of the liver.
52. The system of claim 48, wherein said cut-off value is about
0.84 and an end value, H, greater than or equal to about 0.84 is
indicative of the presence of cirrhosis of the liver.
53. The system of claim 48, wherein said input device is a keyboard
or a cable in data communication with a computer, a network, a
server, or an analytical instrument.
54. The system of claim 48, wherein said output device is selected
from the group consisting of a video display monitor, a printer.
Description
FIELD OF THE INVENTION
[0001] The present invention relates generally to the field of
medical diagnostics, in particular, diagnosis and staging of
hepatic fibrosis.
BACKGROUND OF THE INVENTION
[0002] Liver fibrosis is a gradual process of increased production
and decreased degradation of extracellular matrix materials. It is
generally viewed that damage to hepatic cells initiates the process
of fibrosis formation through activation and secretion of multiple
cellular factors from Kupffer cells (macrophages which line the
liver sinusoids). Such factors, in addition to factors secreted by
damaged hepatocytes, thrombocytes, and endothelial cells of the
hepatic sinusoid and other mediators, activate hepatic stellate
cells. Activated hepatic stellate cells differentiate into
myofibroblasts, which proliferate and synthesize a massive amount
of extracellular materials that gradually accumulate, resulting in
the development of liver fibrosis.
[0003] Liver fibrosis is common to liver diseases of many
etiologies, including chronic viral hepatitis B and C, autoimmune
liver disease, such as autoimmune hepatitis and primary biliary
cirrhosis, alcoholic liver disease, nonalcoholic fatty liver
disease, metabolic disorders, such as lipid, glycogen, or metal
storage disorders, and drug-induced liver disease. The fibrosis
exhibited in these disorders results from chronic insults to the
liver from, for example, viral infection, alcohol, or drugs.
[0004] Hepatitis C, for example, is one of the leading causes of
chronic liver disease in the United States, where an estimated 3.9
million people are chronically infected with hepatitis C virus
(HCV) and approximately 30,000 new cases of acute HCV occur each
year. Thus, the prevalence of hepatitis C is estimated to be 1.8%
in the United States, with as many as 10,000 deaths per year
resulting from chronic HCV infection (Alter, Semin. Liver Dis.
15:5-14 (1995)). World-wide, the prevalence of chronic HCV
infection is estimated to be about 3% (J Viral Hepat 6:35-47
(1999)). Moreover, death, hospitalization and liver transplantation
as a result of chronic hepatitis C have increased significantly in
the past decade (Hepatology 36:S30-42 (2002)). Liver fibrosis is
the main determinant of hepatitis C virus related morbidity and
mortality (Lancet 349:825-323 (1997)). Furthermore, the stage of
fibrosis is prognostic and provides information on the likelihood
of disease progression and response to treatment (Hepatology
36:S47-564, 5 (2002); N Engl J Med 347:975-82 (2002)). The presence
of significant fibrosis (equivalent to METAVIR F2 or greater) as
determined by liver biopsy, is widely accepted as an indication to
commence treatment (Gut 49:11-21 (2001); J Hepatol 31:3-8 (1999);
Hepatology 39:1147-71 (2004)). The presence of cirrhosis has
implications regarding screening for hepatocellular carcinoma and
esophageal varices (J Hepatol 31:3-8 (1999)).
[0005] Liver biopsy is currently the gold standard for staging
fibrosis, but has well documented complications including pain,
bleeding and, rarely, death (Gut 36:437-419, (1995); N Engl J Med
344:495-500 (2001)). Liver biopsy is also expensive, as are the
costs associated with treating any resulting complications. In
addition, inter- and intra-observer error may lead to incorrect
staging (Hepatology 36:S47-564, 5 (2002)), as may sampling error in
up to 33% of biopsies (Am J Gastroenterol 97:2614-8 (2002)).
[0006] Routinely measured serum markers, used either individually
or in combination, have been examined as alternatives to liver
biopsy for staging fibrosis among hepatitis C patients. Platelet
count, ratio of aspartate aminotransferase (AST) to alanine
aminotransferase (ALT), or a combination of AST and platelet count,
are reliable predictors of cirrhosis (Arch Intern Med 163:218-24
(2003)). However, their predictive value for mild or moderate
fibrosis is insufficient to be of clinical utility (Hepatology 38:
518-26 (2003); Hepatology 39: 1456-7 (2004)). More complex models
which include routinely available analytes such as cholesterol,
.gamma.-glutamyltransferase (GGT), platelet count, and prothrombin
time, have a high negative predictive value (NPV) for excluding
significant hepatic fibrosis, but have poor positive predictive
value (PPV) and are only applicable to approximately one third of
patients (Hepatology 39:1456-7 (2004)). A recently reported model
incorporating measures of insulin resistance and past alcohol
intake, reliably predicted significant fibrosis, but was less
accurate in excluding significant fibrosis (Hepatology 39:1239-47
(2004)).
[0007] In efforts to improve the accuracy of noninvasive methods of
staging liver fibrosis, several non-routinely-available biochemical
markers associated with collagen and extra-cellular matrix
deposition/degradation have been examined. Serum levels of
hyaluronic acid, tissue inhibitor of matrix metalloproteinase-1
(TIMP-1) and matrix metalloproteinase-2 (MMP-2) correlate with
liver fibrosis, but by themselves have low predictive value for
diagnosing significant fibrosis (J Gastroenterol Hepatol 15:945-51,
18 (2000); J Hepatol 26:574-83 (1997)). "FibroTest" (BioPredictive
S.A.S., Paris, France), which combines multiple biochemical markers
with age and gender, was accurate in detecting significant fibrosis
in just under half of patients from a center in France (Lancet 357:
1069-75 (2001)). However, when applied to a population of hepatitis
C patients from our institution, FibroTest was less accurate and
had a PPV of less than 80%. (Clin Chem 49: 450-420 (2003))
SUMMARY OF THE INVENTION
[0008] Provided herein are methods of diagnosing the presence and
extent of liver fibrosis in a patient. The method is accomplished
by determining a score based on age, gender, and the concentrations
in serum of .alpha.2-macroglobulin, .gamma.-glutamyl transferase
(GGT), bilirubin, and hyaluronic acid (HA).
[0009] Provided herein are methods of differentiating between
degrees of liver fibrosis; in particular, predicting the presence
of significant fibrosis and predicting the absence of advanced
liver fibrosis in an individual. This method is accomplished by
obtaining a sample from the individual and determining the levels
of four markers, .alpha..sub.2-macroglobulin (.alpha.2MG),
hyaluronic acid (HA), bilirubin, .gamma.-glutamyl transferase
(GGT). The levels of these markers are input into a first equation,
along with age and gender to determine an intermediate value. The
intermediate value is input into a second equation to determine the
end value or Hepascore. The end value is compared to a cut-off
value of about 0.5 (preferably 0.5), wherein the individual is
diagnosed as having significant liver fibrosis when the Hepascore
is greater than or equal to the cut-off value of about 0.5
(preferably 0.5). The individual is diagnosed with no advanced
fibrosis if the Hepascore is less than a cut-off value of about 0.5
(preferably 0.5).
[0010] Fibrosis is scored on the 5-point METAVIR scale as follows:
F0--no fibrosis, F1--portal fibrosis alone, F2--portal fibrosis
with rare septae, F3--portal fibrosis with many septae,
F4--cirrhosis. "Significant fibrosis" corresponds to stages F2, F3,
and F4, while "advanced fibrosis" corresponds to stages F3 and
F4.
[0011] The phrase "intermediate value" as used herein represents a
value, y, calculated from the levels of the four markers, age, and
gender using the following equation:
y=exp(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha..sub.2-macrog-
lobulin)+(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT))
wherein, age is provided in years; male gender=1, female gender=0,
.alpha..sub.2-macroglobulin as reported in g/L; hyaluronic acid as
reported in .mu.g/L; bilirubin as reported in .mu.mol/L; and GGT as
reported in U/L.
[0012] The term "coefficient" as used herein refers to the factors
that each variable (i.e., age, gender, .alpha..sub.2-macroglobulin,
hyaluronic acid, bilirubin, and GGT) is multiplied by in the above
equation.
[0013] The numerical definitions of the constant and the
coefficients in the above equation can be varied and still produce
a valid intermediate value. For example, the constant, -4.185818,
may vary from about -6.846 to about -1.5257; the age coefficient
may vary from about -0.0877 to about 0.0378; the gender coefficient
may vary from about -0.3064 to about 1.7992; the
.alpha..sub.2-macroglobulin coefficient can vary from about 0.4406
to about 1.5672; the hyaluronic acid coefficient can vary from
about 0.0090 to about 0.0515; the bilirubin coefficient can vary
from about -0.0099 to about 0.1482; and the GGT coefficient can
vary from about -0.0055 to about 0.0032.
[0014] One of skill in the art would recognize that the
concentrations of the markers could be provided in units other than
the ones recited above. In this case, one would generate an
equivalent equation to determine the intermediate value by
converting the units as recited above to other units using a
mathematical function. The inverse of that function would be
performed on the coefficient for that marker. For example,
.alpha..sub.2-macroglobulin is reported in g/L. If this marker were
reported in mol/L (i.e., (g/L)/(molecular weight of
.alpha..sub.2-macroglobulin)), one would multiply the coefficient
for .alpha..sub.2-macroglobulin (i.e., 1.0039) by the molecular
weight of .alpha..sub.2-macroglobulin. One of skill in the art
would recognize that in a case in which there is more than one
molecular weight for a given marker, one particular molecular
weight must be selected and used for both of the above described
mathematical functions. The new coefficient would be used in the
equation.
[0015] The phrases "end value" and "Hepascore" are used
interchangeably herein. The Hepascore, H, is a number calculated
from the intermediate value using the equation below and ranges
from 0.0 to 1.0. H=y/(1+y) The Hepascore is compared with a cut-off
value in order to determine the extent of fibrosis. In a particular
aspect, a Hepascore greater than or equal to a cut-off value of
about 0.5 (preferably 0.5) is predictive of significant fibrosis,
or stage F2-F4. A Hepascore less than a cut-off value of about 0.5
(preferably 0.5) is predictive of the absence of advanced fibrosis
(stages F3 and F4). A Hepascore less than a cut-off value of about
0.84 (preferably 0.84) is predictive of the absence of cirrhosis
(stage F4).
[0016] In another aspect, a Hepascore is used as a positive
predictor of cirrhosis. In this aspect, a Hepascore greater than or
equal to a cut-off value of about 0.84 (preferably 0.84) is
indicative of the presence of cirrhosis.
[0017] The phrase "cut-off value" as used herein refers to a
Hepascore value that is statistically predictive of a symptom or
disease or lack thereof. In a particular aspect, the cut-off value
is about 0.5 and the Hepascore distinguishes between significant
fibrosis and an absence of advanced fibrosis. For example, a
Hepascore greater than or equal to a cut-off value of about 0.5 is
predictive of significant fibrosis. A Hepascore less than a cut-off
value of about 0.5 is predictive of an absence of advanced
fibrosis. In certain embodiments, this cut-off value may be between
0.425 to 0.575 inclusive, or between 0.450 to 0.550 inclusive, or
between 0.475 to 0.525 inclusive. Alternatively, the cut-off value
may be 0.425, 0.450, 0.5 0.475, 0.525, 0.550, and even 0.575. The
above numbers are subject to 5% variation.
[0018] In another aspect, the cut-off value is about 0.84, more
preferably 0.84 and the Hepascore can distinguish between the
presence or absence of cirrhosis. For example, a Hepascore greater
than or equal to about 0.84 (preferably 0.84) is predictive of
cirrhosis. In certain embodiments, this cut-off value may be
between 0.70 to 0.95 inclusive, or between 0.75 to 0.90 inclusive,
or between 0.80 to 0.85 inclusive. Alternatively, the cut-off value
may be 0.95, 0.90, 0.84, 0.80, 0.75, and even 0.70. The above
numbers are subject to 5% variation.
[0019] The term "about" as used herein in reference to numbers or
quantitative measurements, refers to the indicated value plus or
minus 10%.
[0020] Also provided herein are methods of monitoring progression
of liver fibrosis in a patient suffering from a liver disease. This
method is accomplished by obtaining a first sample from the
individual and a second sample from the same individual, at a time
after the first sample. The levels of four markers,
.alpha..sub.2-macroglobulin (.alpha.2MG), hyaluronic acid (HA),
bilirubin, .gamma.-glutamyl transferase (GGT) are determined in
each sample. These levels are input into a first equation, along
with age and gender, to determine an intermediate value
corresponding to each sample. The intermediate value is input into
a second equation to determine the an end value or Hepascore,
corresponding to each sample. The end values are compared to a
cut-off value to determine the extent of liver fibrosis. A
Hepascore greater than or equal to a cut-off value of about 0.5 is
predictive of significant fibrosis. A Hepascore less than a cut-off
value of about 0.5 (preferably 0.5) is predictive of an absence of
advanced fibrosis. In certain embodiments, this cut-off value may
be between 0.425 to 0.575 inclusive, or between 0.450 to 0.550
inclusive, or between 0.475 to 0.525 inclusive. Alternatively, this
cut-off value may be 0.425, 0.450, 0.475, 0.5, 0.525, 0.550, and
even 0.575. The above numbers are subject to 5% variation. A
Hepascore greater than or equal to about 0.84 is indicative of
cirrhosis, whereas a Hepascore less than about 0.84 is indicative
of an absence of cirrhosis. In certain embodiments, this cut-off
value may be between 0.70 to 0.95 inclusive, or between 0.75 to
0.90 inclusive, or between 0.80 to 0.85 inclusive. Alternatively,
this cut-off value may be 0.95, 0.90, 0.84, 0.80, 0.75, and even
0.70. The above numbers are subject to 5% variation. The extent of
liver fibrosis (e.g., significant fibrosis, cirrhosis, or an
absence of advanced fibrosis) as indicated by the first sample is
compared to the extent of liver fibrosis indicated by the second
sample; wherein an increase in the extent of liver fibrosis in the
second sample as compared with the first indicates progression of
liver fibrosis, whereas a decrease in the extent of liver fibrosis
in the second sample as compared to the first indicates a
regression of liver fibrosis.
[0021] Further provided herein are methods of monitoring the
efficacy a liver fibrosis therapy in a patient suffering from a
liver disease. This method is accomplished by obtaining a first
sample from the individual and a second sample from the same
individual, at a time after the first sample. The levels of four
markers, .alpha.-macroglobulin (.alpha.2MG), hyaluronic acid (HA),
bilirubin, .gamma.-glutamyl transferase (GGT) are determined in
each sample. These levels are input into a first equation, along
with age and gender, to determine an intermediate value
corresponding to each sample. The intermediate value is input into
a second equation to determine an end value or Hepascore,
corresponding to each sample. The end values are compared to a
cut-off value to determine the extent of liver fibrosis. A
Hepascore greater than or equal to a cut-off value of about 0.5
(preferably 0.5) is predictive of significant fibrosis. A Hepascore
less than a cut-off value of about 0.5 (preferably 0.5) is
predictive of an absence of advanced fibrosis. In certain
embodiments, this cut-off value may be between 0.425 to 0.575
inclusive, or between 0.450 to 0.550 inclusive, or between 0.475 to
0.525 inclusive. Alternatively, this cut-off value may be 0.425,
0.450, 0.475, 0.5, 0.525, 0.550, and even 0.575. The above numbers
are subject to 5% variation. A Hepascore greater than or equal to
about 0.84 is indicative of cirrhosis, whereas a Hepascore less
than about 0.84 is indicative of an absence of cirrhosis. In
certain embodiments, this cut-off value may be between 0.70 to 0.95
inclusive, or between 0.75 to 0.90 inclusive, or between 0.80 to
0.85 inclusive. Alternatively, this cut-off value may be 0.95,
0.90, 0.84, 0.80, 0.75, and even 0.70. The above numbers are
subject to 5% variation. The extent of liver fibrosis (e.g.,
significant fibrosis, cirrhosis, or an absence of advanced
fibrosis) as indicated by the first sample is compared to the
extent of liver fibrosis indicated by the second sample; wherein
either no change or an increase in the extent of liver fibrosis in
the second sample as compared with the first indicates the liver
fibrosis therapy is not efficacious, whereas a decrease in the
extent of liver fibrosis in the second sample as compared to the
first indicates the liver fibrosis therapy is efficacious.
[0022] One of skill in the art would recognize that in monitoring
liver fibrosis therapy, one could compare samples taken before
treatment is initiated to those samples taken after therapy is
concluded. One could also compare two samples taken at different
times during treatment. One could also compare a sample taken
during treatment with one taken after therapy is concluded.
[0023] The term "therapy" as used herein refers to any manner of
treatment of a disease or symptoms thereof. Therapy of liver
fibrosis includes any accepted or experimental treatment. Therapy
may include treatment or removal of the causal agent or treatment
of the fibrosis with drug compounds or other therapeutic
agents.
[0024] The terms "efficacy" or "efficacious" as used herein refers
to the ability of a drug, therapy or treatment to relieve symptoms
or eliminate the disease. A treatment is said to have efficacy if
certain positive outcomes, for example, a regression of extent of
liver fibrosis, occur as a result of the treatment.
[0025] Invention methods may be used for a patient suffering from
any disease involving liver fibrosis. In particular, the method of
the invention can be performed for detecting liver fibrosis in
patients suffering from, for example, hepatitis B, hepatitis C,
alcoholism and alcohol abuse, alcoholic liver disease,
hemochromatosis, metabolic disease, diabetes, obesity, autoimmune
hepatitis, nonalcoholic fatty liver disease, alcoholic fatty liver,
drug-induced liver disease, primary biliary cirrhosis, primary
sclerosing cholangitis, .alpha.1-antitrypsin deficiency, Wilson
disease, and chronic rejection or recurrent liver disease following
liver transplantation.
[0026] In a particular aspect, are used to evaluate patients
infected with chronic viral hepatitis infection (e.g., hepatitis B
or C virus), in particular, the hepatitis C virus. In yet another
embodiment, the individual is co-infected with at least two
viruses, including, for example, one or more of the following:
hepatitis B, hepatitis C, hepatitis D and HIV-1.
[0027] Alcoholic liver disease consists of a spectrum of diseases
from alcoholic fatty liver (i.e., steatosis), to alcoholic
hepatitis to cirrhosis. Each of these conditions are pathologically
distinct and any or all of these three conditions can occur
together in the same patient. Alcoholic fatty liver is
characterized by an accumulation of fat within the hepatocytes as a
result of alcohol abuse. Fatty liver can be accompanied by
inflammation (i.e., steatohepatitis), which can lead to scarring of
the liver and cirrhosis. Alcoholic hepatitis may occur separately
or in combination with cirrhosis, with a range of severity. This
condition is characterized by liver cell necrosis and an
inflammatory reaction. Histologically, alcoholic hepatitis is
characterized by hepatocytes that are swollen as a result of an
increase in intracellular water secondary to increase in cytosolic
proteins. Steatosis, often of the macrovesicular type, is present.
Cirrhosis is the most severe form of liver disease and occurs when
damaged cells are replaced by connective tissue, resulting in
scarring of the liver, and eventually liver failure.
[0028] Nonalcoholic fatty liver disease (NAFLD) is a condition that
occurs predominately in subjects who are overweight or have glucose
intolerance and do not use excessive amounts of alcohol. NAFLD
refers to a wide spectrum of liver disease ranging from simple
fatty liver (steatosis), to nonalcoholic steatohepatitis (NASH), to
cirrhosis (irreversible, advanced scarring of the liver). All of
the stages of NAFLD have in common the accumulation of fat (fatty
infiltration) in the hepatocytes. In NASH, the fat accumulation is
associated with varying degrees of inflammation (hepatitis) and
scarring (fibrosis) of the liver. The term "nonalcoholic" is used
because NAFLD and NASH occur in individuals who do not consume
excessive amounts of alcohol, however, liver biopsy samples are
histologically similar to liver biopsies from patients having liver
disease as a result of an excessive intake of alcohol.
[0029] In a particular aspect, invention methods are used to
evaluate patients diagnosed with or suspected of having fatty liver
disease as a result of alcohol abuse or nonoalcoholic fatty liver
disease.
[0030] The patient population to which the invention pertains is
preferably patients receiving tertiary care such as in a tertiary
care setting, although patients receiving primary and secondary
care also can be evaluated using the invention methods. As used
herein the term "primary care facility" means a facility that
offers first-contact health care only. As used herein the term
"secondary care" refers to services provided by medical specialists
who generally do not have first contact with patients (e.g.,
cardiologist, urologists, dermatologists) such typically occurs in
a local (or community) hospitals setting. As used herein, the term
"tertiary care facility" means a facility that receives referrals
from both primary and secondary care levels and usually offers
tests, treatments, and procedures that are not available elsewhere.
Thus, in a preferred embodiment, the individual to be tested is
receiving tertiary medical care. In further embodiments, the
individual to be tested is receiving primary or secondary medical
care.
[0031] The patient population to which the invention pertains is
preferably patients receiving tertiary care such as in a tertiary
care setting, although patients receiving primary and secondary
care also can be evaluated using the invention methods. As used
herein the term "primary care facility means a facility that offers
first-contact health care only. As used herein the term "secondary
care refers to services provided by medical specialists who
generally do not have first contact with patients (eg,
cardiologist, urologists, dermatologists) such typically occurs in
a local (or community) hospitals setting. As used herein, the term
"tertiary care facility means a facility that receives referrals
from both primary and secondary care levels and usually offers
tests, treatments, and procedures that are not available elsewhere.
Thus, in a preferred embodiment, the individual to be tested is
receiving tertiary medical care.
[0032] The term "disease" as used herein refers to an interruption,
cessation, or disorder of body functions, systems, or organs and is
characterized usually by a recognized etiologic agent(s), an
identifiable group of signs and symptoms, or consistent anatomical
alterations.
[0033] The term "symptom" as used herein refers to an indication or
sign that a person has a disease and include changes from normal
anatomical structure or bodily function.
[0034] Provided herein are methods of differentiating between
degrees of necroinflammatory activity; in particular,
distinguishing between no to mild activity and moderate to severe
activity. This method is accomplished by obtaining a sample of
serum from the individual and determining the levels of four
markers, .alpha..sub.2-macroglobulin (.alpha.2MG), hyaluronic acid
(HA), bilirubin, .gamma.-glutamyl transferase (GGT). The levels of
these markers are input into a first equation, along with age and
gender to determine an intermediate value (y) wherein, y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha.12-macroglobulin)+-
(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT)) and
wherein, age is provided in years; male gender=1, female gender=0,
.alpha..sub.2-macroglobulin as reported in g/L; hyaluronate as
reported in .mu.g/L; bilirubin as reported in .mu.mol/L; and GGT as
reported in U/L. The intermediate value, y, is input into a second
equation to determine the end value or Hepascore (H) wherein,
H+y/(1+y) A Hepascore greater than or equal to a cut-off value of
about 0.5 is predictive of moderate to severe necroinflammatory
activity. A Hepascore less than a cut-off value of about 0.5
(preferably 0.5) is predictive of no activity to mild
necroinflammatory activity. In certain embodiments, this cut-off
value may be between 0.425 to 0.575 inclusive, or between 0.450 to
0.550 inclusive, or between 0.475 to 0.525 inclusive.
Alternatively, this cut-off value may be 0.425, 0.450, 0.475, 0.5,
0.525, 0.550, and even 0.575. The above numbers are subject to 5%
variation.
[0035] Necroinflammatory activity is based upon an assessment of
piecemeal and lobular necrosis and can be graded on a four-point
METAVIR scale as follows: A0--no activity, A1--mild activity,
A2--moderate activity, A3--severe activity.
[0036] As used herein the terms "level" or "concentration" of a
marker are used interchangeably and refer to the relative or
absolute amount or activity of the marker per unit volume by any
direct or indirect measurement. One of skill in the art would
recognize that any assay useful for determining the level of a
marker may be used in invention methods, provided such methods
produce a level comparable to that obtained with the preferred
methods described herein.
[0037] In another aspect, provided herein is a system for
diagnosing the presence of liver fibrosis in an individual. This
system comprises an input device in data communication with a
processor, which is in data communication with an output
device.
[0038] The input device is used for entry of data including levels
of .alpha..sub.2-macroglobulin, hyaluronic acid, bilirubin, and
.gamma.-glutamyl transferase as determined from a sample from the
individual, and data for age and gender. Data may be entered
manually by an operator of the system using a keyboard or keypad.
Alternatively, data may be entered electronically, when the input
device is a cable in data communication with a computer, a network,
a server, or analytical instrument.
[0039] The processor comprises software for computing an end value
or Hepascore, H, and using the end value to diagnose liver
fibrosis. The processor computes the Hepascore, H, using an
algorithm, wherein the algorithm is H=y/(1+y)
[0040] wherein, y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha.2-macroglobulin)+(-
0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT))
[0041] wherein, [0042] age is in years, [0043] male gender=1,
female gender=0, [0044] .alpha..sub.2-macroglobulin is in g/L,
[0045] hyaluronic acid is in .mu.g/L, [0046] bilirubin is in
.mu.mol/L, and [0047] GGT is in U/L. The processor further compares
the end value or Hepascore to a cutoff value to diagnose the
presence of liver fibrosis, wherein a Hepascore greater than or
equal to a cut-off value of about 0.5 is predictive of significant
fibrosis. A Hepascore less than a cut-off value of about 0.5
(preferably 0.5) is predictive of an absence of advanced fibrosis.
In certain embodiments, this cut-off value may be between 0.425 to
0.575 inclusive, or between 0.450 to 0.550 inclusive, or between
0.475 to 0.525 inclusive. Alternatively, this cut-off value may be
0.425, 0.450, 0.475, 0.5, 0.525, 0.550, and even 0.575. The above
numbers are subject to 5% variation. A Hepascore greater than or
equal to about 0.84 is indicative of cirrhosis, whereas a Hepascore
less than about 0.84 is indicative of an absence of cirrhosis. In
certain embodiments, this cut-off value may be between 0.70 to 0.95
inclusive, or between 0.75 to 0.90 inclusive, or between 0.80 to
0.85 inclusive. Alternatively, this cut-off value may be 0.95,
0.90, 0.84, 0.80, 0.75, and even 0.70. The above numbers are
subject to 5% variation.
[0048] The data output device, in data communication with the
processor, receives the diagnosis from the processor and provides
the diagnosis to the system operator. The output device can consist
of, for example, a video display monitor or a printer.
[0049] As used herein, the term "specificity" means the probability
that a diagnostic method of the invention gives a negative result
when the sample is not positive, for example, of significant
fibrosis (i.e., stage F2-F4). Specificity is calculated as the
number of true negative results divided by the sum of the true
negatives and false positives. Specificity is essentially a measure
of how well a method excludes those who do not have a disease or
symptom (e.g., significant fibrosis).
[0050] The term "sensitivity," as used herein, refers to the
characteristic of a diagnostic test that measures the ability of a
test to detect a disease (or symptom) when it is truly present.
Thus, sensitivity is the proportion of all diseased patients for
whom there is a positive test, and is determined as the number of
true positives divided by the sum of true positives and false
negatives.
[0051] The phrase "negative predictive value," as used herein, is
synonymous with "NPV" and means the probability that an individual
diagnosed as not having fibrosis actually does not have the
disease. Negative predictive value can be calculated as the number
of true negatives divided by the sum of the true negatives and
false negatives. Negative predictive value is determined by the
characteristics of the diagnostic method as well as the prevalence
of fibrosis in the population analyzed.
[0052] The phrase "positive predictive value," as used herein, is
synonymous with "PPV" and means the probability that an individual
diagnosed as having fibrosis actually has the disease or symptom.
Positive predictive value can be calculated as the number of true
positives divided by the sum of the true positives and false
positives. Positive predictive value is determined by the
characteristics of the diagnostic method as well as the prevalence
of fibrosis in the population analyzed.
[0053] As used herein, the term "accuracy" means the overall
agreement between the diagnostic method and the disease state.
Accuracy is calculated as the sum of the true positives and true
negatives divided by the total number of sample results and is
affected by the prevalence of fibrosis in the population
analyzed.
BRIEF DESCRIPTION OF THE FIGURES
[0054] FIG. 1A-C: Receiver operating characteristic (ROC) curves of
Hepascore for training and validation set for significant fibrosis,
F2-F4, (FIG. 1A); advanced fibrosis, F3 and F4, (FIG. 1B); and
cirrhosis, F4 (FIG. 1C). The AUC between the training and
validation sets was not significantly different for significant
fibrosis (P=0.6), advanced fibrosis (P=0.2) or cirrhosis
(P=0.4).
[0055] FIG. 2: Box plots of Hepascore according to fibrosis stage
in the training set (n=117). Hepascore ranges from 0.0-1.0.
Fibrosis staged according to METAVIR. Middle line represents
median, inferior and superior ends of boxes represent 25.sup.th and
75.sup.th percentile respectively. Whiskers are 25.sup.th and
75.sup.th percentile.+-.1.53*interquartile range. Dots represent
outliers.
[0056] FIG. 3: Application of Hepascore Fibrosis Model to the
Validation Set (n=104).
DETAILED DESCRIPTION OF THE INVENTION
[0057] Provided herein are methods of diagnosis of liver fibrosis
and monitoring the progression or treatment of liver fibrosis in a
patient comprising the steps of:
[0058] a) measuring the levels of four biochemical markers (i.e.,
.alpha.2-macroglobulin, .gamma.-glutamyl transferase (GGT),
bilirubin, and hyaluronic acid (HA)) in a sample from the
patient,
[0059] b) combining the values for each marker, age, and gender in
an equation that gives a weight to each factor to determine an
intermediate value,
[0060] c) determining an end value or Hepascore using the
intermediate value in a second equation,
[0061] d) comparing the end value to a cut-off value in order to
determine the presence or extent of liver fibrosis.
[0062] Samples
[0063] As used herein, the term "sample" refers to a biological
specimen that may contain one or more markers such as .alpha.2MG,
HA, bilirubin, or GGT. In particular aspects, serum is the sample.
In other aspects, plasma is the sample. Plasma further containing
anticoagulants or preservatives may be used provided the marker
levels obtained therefrom are comparable to the marker levels
obtained from serum.
[0064] One skilled in the art would understand that the levels of
the four markers may be assayed in a single sample or may each be
assayed from a separate sample, provided that the samples are
obtained on the same day. The separate samples may be the same type
of sample (e.g., serum) or may be of different types (e.g., serum
and plasma). In a particular aspect, .alpha.2MG, HA, bilirubin, and
GGT each are assayed in the same serum sample.
[0065] Determination of Marker Levels
[0066] .alpha..sub.2-Macroglobulin
[0067] The preferred method for determining
.alpha..sub.2-macroglobulin (.alpha.2MG) levels is by nephelometry
using the IMMAGE Immunochemistry System (Beckman Coulter). In this
method, .alpha.2MG in the sample and an antibody against .alpha.2MG
applied to the sample form .alpha.2MG-antibody aggregates. The
IMMAGE system measures the rate of increase in light scattered from
particles suspended in solution as a result of complexes formed
during the above .alpha.2MG-antibody reaction. Reagents for this
assay are provided with the IMMAGE system and the assay is run per
the manufacturer's protocol. Briefly, reagents, calibrator (Beckman
Calibrator 2), controls and samples are loaded into the system. The
automated system adds 21 .mu.L anti-.alpha.2MG antibody, 300 .mu.L
Buffer 1, and 20.42 .mu.L Diluent-1 to 0.58 .mu.L sample. The
system calculates the level of .alpha.2MG in the sample and reports
the result in g/L.
[0068] Other methods of determining .alpha..sub.2-macroglobulin
levels may be used provided such methods provide a level comparable
to that obtained by the preferred method. Such methods are
well-known in the art and include, for example, immunoassays,
including radioimmunoassay, enzyme-linked immunoassay (ELISA), and
two-antibody sandwich assays may be used in invention methods.
Monoclonal and polyclonal anti-.alpha.2MG antibodies useful in
immunoassays can be readily obtained from a variety of sources.
[0069] Hyaluronic Acid
[0070] Hyaluronic acid (HA), also known as hyaluronate or
hyaluronan, is a high molecular weight polysaccharide with an
unbranched backbone comprised of dimeric units consisting of
glucuronic acid and .beta.-(1,3)-N-acetylglucosamine moieties
connected by .beta.-1,4 linkages. Hyaluronic acid can have a length
of a few such dimeric units to more than 1,000, with each dimeric
unit having a molecular weight of about 450 D. Hyaluronic acid is
produced primarily by fibroblasts and other specialized connective
tissue cells and plays a structural role in the connective tissue
matrix. Hyaluronic acid is widely distributed throughout the body
and can be found as a free molecule in, for example, plasma,
synovial fluid, and urine.
[0071] Levels of HA are preferably determined using an
enzyme-linked protein binding assay commercially available assay
from Corgenix (Westminster, Colo.). This test is a sandwich protein
binding assay which employs hyaluronic acid binding protein (HABP)
as the capture molecule. In this assay, diluted serum or plasma and
HA reference solutions are incubated in HABP-coated microwells. HA
present in samples is captured by the immobilized binding protein
(HABP). Unbound serum components are removed by washing, and HABP
conjugated with horseradish peroxidase (HRP) solution is added to
the microwells and complexes with bound HA. Unbound conjugated HABP
is removed by washing and a chromogenic substrate of
tetramethylbenzidine and hydrogen peroxide is added to develop a
colored reaction. The intensity of the color is measured in optical
density (O.D.) units with a spectrophotometer at 450 nm. Optical
density is converted to HA concentration using a standard
curve.
[0072] The procedure for the hyaluronic acid test from Corgenix is
as follows. HA reference solutions and reagent blank are assayed in
duplicate. Duplicate determinations are also recommended for
patient samples. Reaction Buffer without serum is used for the
reagent blank, which represents the 0 ng/mL HA reference solution.
A water blank is included with each plate using 200 .mu.L of
reagent grade water, which is added at the completion of the assay,
immediately prior to reading the plate. The water blank is to be
used to zero the plate reader. Any microwell strips that will not
be used in the run from the frame are removed and the foil pouch
resealed. HA reference solutions and patient samples are prepared
by adding 1 part of the solution or sample to 10 parts Reaction
Buffer (blue solution). 100 .mu.L of diluted HA reference
solutions, patient samples, or reaction buffer (for reagent blank)
is added to appropriate microwells. The well for the water blank is
left empty. The plate is incubated for 60 minutes at room
temperature. After the incubation is complete, the microwells are
inverted to dump contents into a suitable container. Do not allow
samples to contaminate other microwells. The wells are washed 4
times with working wash solution (PBS), filling wells completely.
PBS in the water blank well will not interfere with the procedure.
The microwells are inverted between each wash to empty fluid. Use a
snapping motion of the wrist to shake the liquid from the wells.
Pound and/or blot on absorbent paper to remove residual wash
buffer. Do not allow wells to dry out between steps. 100 .mu.L
HRP-conjugated HABP Solution (red solution) is added to all wells
except the water blank. The plate is incubated for 30 minutes at
room temperature. After the incubation is complete, the microwells
are carefully invert to dump conjugate solution and washed 4 times
with PBS. Do not allow the wells to dry out. 100 .mu.L
One-component Substrate Solution is added to each well (except the
water blank well) and the plate is incubated for 30 minutes at room
temperature. Add substrate solution to wells at a steady rate. Blue
color will develop in wells with positive samples. 100 .mu.L
Stopping Solution (0.36 N sulfuric acid) is added to each well
(except the water blank well) to stop the enzymatic reaction. The
stopping solution is added to the wells in the same order and at
the same rate as the substrate solution. The stopping solution is
not added to the water blank well, instead, 200 .mu.L of reagent
grade water is added to the water blank well. The plate reader is
zeroed against the water blank well. The optical density (O.D.) of
each well are read at 450 nm (650 nm reference). The O.D. of wells
should be measured within one hour after the addition of stopping
solution. The results are calculated as follows. The mean O.D.
values of duplicate wells of HA reference solutions, reagent blanks
and patient samples are calculated. The best fit curve using the
mean O.D.s of the 0 ng/mL (reagent blank), 50, 100, 200, 500, and
500 ng/mL reference solutions is generated using either third order
polynomial regression (recommended), linear regression or hand
plotting. A new curve is plotted with each assay run. The HA
concentrations (ng/mL) in patient samples can be determined from
this curve.
[0073] Other methods of determining hyaluronic acid levels may be
used provided such methods provide a level comparable to that
obtained by the preferred method. Such methods are well-known in
the art and include, for example, a variety of competitive and
non-competitive binding assays and immunoassays. Competitive
binding assays using .sup.125I-labeled HA binding protein;
competitive binding assays based on alkaline phosphatase
labeled-hyaluronectin (HN); and non-competitive binding assays
based on peroxidase-labeled proteoglycan or peroxidase-labeled
HA-binding protein, among others, are well-known in the art. See,
for example, Lindquist et al., Clin. Chem. 38:127-132 (1992);
Delpech and Bertrand, Anal. Biochem. 149:555-565 (1985);
Engstrom-Laurent et al., Scand. J. Clin. Lab. Invest. 45:497-504
(1985); Brandt et al., Acta Otolaryn. 442 (Suppl.):31-35 (1987);
Goldberg, Anal. Biochem. 174:448-458 (1988); Chichibu et al., Clin.
Chim. Acta 181:317-324 (1989); Li et al., Conn. Tissue Res.
19:243-254 (1989); Poole et al., Arth. Rheum. 33:790-799 (1990);
Poole et al., J. Biol. Chem. 260:6020-6025 (1985); and Laurent and
Tengblad, Anal. Biochem. 109:386-394 (1980)). A variety of
immunoassay formats may be used to determine a level of HA,
including radioimmunoassays and enzyme-linked immunoassays.
Polyclonal or monoclonal anti-HA antibodies useful in immunoassays
are commercially available from a variety of sources.
[0074] Bilirubin
[0075] Bilirubin is a chemical formed from the degradation of heme
(a component of the hemoglobin present in red blood cells).
Bilirubin in the blood is taken up by the liver, chemically
modified in a process called conjugation, and secreted into the
bile. The phrase "direct bilirubin" refers to conjugated bilirubin,
whereas "indirect bilirubin" refers to unconjugated bilirubin.
"Total bilirubin" refers to conjugated and unconjugated
bilirubin.
[0076] Bilirubin levels are preferably determined from on fresh
serum, within 36 hours of collection, using an automated
biochemistry analyzer (Hitachi 917, Roche Diagnostics, Mannheim,
Germany). In this method, total bilirubin, in the presence of a
solubilizing agent, is coupled with a diazonium ion in a strongly
acidic medium (pH 1-2) to form azobilirubin. The intensity of the
color of the azobilirubin produced can be measured photometrically
and is proportional to the total bilirubin in the sample. Samples,
controls, and reagents are placed into the analyzer, the assay is
run, and the results are automatically calculated. The results are
reported in mg/dL, which can be converted to .mu.mol/L by
multiplying by a factor of 17.1.
[0077] Bilirubin levels can be assayed by other methods known in
the art, provided such methods produce a level that is comparable
to a level obtained using the preferred method. Such methods
include, analyzing total bilirubin using diazotized sulfanilic acid
reagent with blank correction (Malloy and Evelyn method; Abbott
Laboratories and Ciba Corning). In another method, a sample is
mixed with the reagent containing the detergent and the vanadate,
at approximately pH 3, oxidizing the total bilirubin in the sample
to biliverdin. The total bilirubin concentration in the sample can
be obtained by measuring the absorbance before and after the
vanadate oxidation (Total Bilirubin V assay; Wako Chemicals Inc.,
Richmond, Va.).
[0078] .gamma.-Glutamyl Transferase
[0079] .gamma.-glutamyl transferase (GGT), sometimes called
.gamma.-glutamyl transpeptidase (GGPT), is an enzyme that is
compared with alkaline phosphatase (ALP) levels to distinguish
between skeletal disease and liver disease. Because GGT is not
increased in bone disorders, as is ALP, a normal GGT with an
elevated ALP would indicate bone disease. Conversely, because the
GGT is more specifically related to the liver, an elevated GGT with
an elevated ALP would strengthen the diagnosis of liver or
bile-duct disease.
[0080] GGT levels are preferably determined using an automated
biochemistry analyzer such as Hitachi 917 biochemistry analyzer
(Mannheim, Germany) with Roche Diagnostics reagents. In this
method, GGT is measured in fresh serum within 36 hours of
collection using this procedure. R1 reagent (123 mmol/L TRIS (i.e.,
tris(hydroxymethyl)-aminomethane) buffer, pH 8.25 (25.degree. C.);
123 mmol/L glycylglycine; preservative; additive) is added to the
sample. R2 reagent (10 mmol/L acetate buffer, pH 4.5 (25.degree.
C.); 25 mmol/L L-.gamma.-glutamyl-3-carboxy-4-nitroanilide;
stabilizer; preservative) is added to start the formation of
L-.gamma.-glutamyl-glycylglycine and 5-amino-2-nitrobenzoate from
L-.gamma.-glutamyl-3-carboxy-4-nitroanilide and glycylglycine in
the presence of GGT. Gamma-glutamyltransferase transfers the
.gamma.-glutamyl group of
L-.gamma.-glutamyl-3-carboxy-4-nitroanilide to glycylglycine. The
amount of 5-amino-2-nitrobenzoate liberated is proportional to the
GGT activity and can be measured photometrically. Samples,
controls, and reagents are placed into the analyzer, set up to run
according to the manufacturer's protocol, the assay is run, and the
results are automatically calculated. The results are reported in
U/L, which can be converted to .mu.kat/L by multiplying by a factor
of 0.0167.
[0081] GGT levels can be determined by other methods known in the
art provided such methods produce a result comparable to that
obtained with the preferred method.
[0082] Determination of a Hepascore
[0083] Levels of the markers as determined above, along with age
and gender, are input in the following equation to determine an
intermediate value, y. y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha.2-macroglobulin)+(-
0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT)) wherein,
age is provided in years; male gender=1, female gender=0,
.alpha..sub.2-macroglobulin as reported in g/L; hyaluronate as
reported in .mu.g/L; bilirubin as reported in 1 mol/L; and GGT as
reported in U/L.
[0084] The Hepascore, H, is calculated using the intermediate
value, y, in the following equation: H=y/(1+y)
[0085] Determination of Presence and Stage of Liver Fibrosis
[0086] The end value or Hepascore, H, is compared to a cut-off
value, in order to identify significant fibrosis (METAVIR stages F2
to F4), cirrhosis (stage F4) or an absence of advanced fibrosis
(stages F3 and F4).
[0087] Significant fibrosis (stages F2 to F4) can be distinguished
from an absence of advanced fibrosis (F3 and F4). A Hepascore
greater than or equal to a cut-off value of about 0.5 (preferably
0.5) is indicative of significant fibrosis, whereas, a Hepascore
less than a cut-off value of about 0.5 (preferably 0.5) is
indicative of an absence of advanced fibrosis. A Hepascore of
greater than or equal to a cut-off value of about 0.84 (preferably
0.84) is indicative of cirrhosis, whereas a Hepascore of less than
a cut-off value of about 0.84 (preferably 0.84) is indicative of
the absence of cirrhosis.
[0088] Determination of Presence and Degree of Necroinflammatory
Activity
[0089] The end value or Hepascore, H, is compared to a cut-off
value, in order to distinguish no/mild necroinflammatory activity
from moderate/severe necroinflammatory activity. A Hepascore
greater than or equal to a cut-off value of about 0.5 (preferably
0.5) is indicative of moderate/severe necroinflammatory activity,
whereas, a Hepascore less than about 0.5 (preferably 0.5) is
indicative of no/mild necroinflammatory activity.
[0090] The following examples serve to illustrate the present
invention. These examples are in no way intended to limit the scope
of the invention.
EXAMPLE 1
[0091] Selection of Patient Population. Patients were prospectively
recruited from viral liver clinics in different tertiary referral
centers; the training set was recruited from Sir Charles Gairdner
Hospital (Perth, Australia) and the validation set from Westmead
Hospital and Royal Prince Alfred Hospital (Sydney, Australia). All
patients had detectable hepatitis C RNA at the time of evaluation
and were treatment naive. Coexisting liver disease due to hepatitis
B, haemochromatosis, alpha-1 antitrypsin deficiency, Wilson's
disease, autoimmune and cholestatic liver diseases were excluded by
standard clinical, laboratory, imaging and histological studies. No
patient had human immunodeficiency virus co-infection or had
undergone liver transplantation. Liver biopsy was performed as part
of the routine clinical care of these patients. Age, gender and
viral genotype were recorded at time of liver biopsy. Patients from
the training set had the Fibrotest calculated.
[0092] The demographic and biochemical characteristics of the
training (n=117) and validation sets (n=104) were generally similar
(Table 1), but the validation set had a lower proportion of
patients with genotype 1 (48% vs. 61%) and more genotype 4 patients
(5% vs. 0%). There was also a trend towards a greater proportion of
patients in the validation set having significant fibrosis (P=0.05)
but not advanced fibrosis (P=0.4). The median portal tract number
was 9 and the median biopsy length was 13 mm. The inter-observer
agreement between pathologists was good (Kappa statistic,
.kappa.=0.56) for METAVIR staging and for significant fibrosis
(Kappa statistic, .kappa.=0.72). TABLE-US-00001 TABLE 1 Clinical
and laboratory features of the training and validation cohorts
Tranining Set Validation Set Variable (n = 117) (n = 104) P value
Age, years, mean (SD) 40 (9) 41 .+-. 9 0.5 Female, n (%) 38 (32%)
28 (27%) 0.4 Genotype 1, n (%) 67 (61%) 50 (48%) Genotype 2/3, n
(%) 45 (39%) 48 (47%) Genotype 4, n (%) 0 5 (5%) 0.03 ALT, U/L 124
.+-. 90 131 .+-. 99 0.5 Bilirubin, .mu.mol/L 12 .+-. 8 12 .+-. 5
0.5 Albumin, g/L 42 .+-. 4 42 .+-. 3 0.7 Stage F0, n (%) 23 (19%)
17 (16%) Stage F1, n (%) 43 (37%) 28 (27%) Stage F2, n (%) 29 (25%)
35 (34%) Stage F3, n (%) 15 (13%) 7 (7%) Stage F4, n (%) 7 (6%) 17
(16%) 0.03 Significant Fibrosis, 51 (44%) 59 (57%) 0.05 F2 to F4, n
(%) Advanced Fibrosis, 22 (19%) 24 (23%) 0.4 F3 and F4, n (%) Grade
A0, n (%) 20 (17%) 8 (8%) 0.001 Grade A1, n (%) 75 (64%) 63 (60%)
Grade A2, n (%) 13 (11%) 32 (31%) Grade A3, n (%) 9 (8%) 1 (1%)
Significant Activity, 22 (19%) 33 (32%) 0.03 A2 and A3, n (%)
Histology scored according to METAVIR. Genotype not available for
five patients in the training set and one patient in the validation
set.
EXAMPLE 2
[0093] Assay of Markers. Training set sera were analyzed for 10
candidate markers. Bilirubin, ALT, GGT, and albumin were all
measured on fresh serum within 36 hours of collection using an
automated biochemistry analyzer (Hitachi 917, Roche Diagnostics,
Mannheim, Germany). Other analyses were performed in batches using
frozen serum stored at -20 C. TIMP-1 and MMP-2 were measured by
enzyme-linked immunosorbent assay on a 96-well microplate (Biotrak,
Amersham Biosciences, Bucks, UK). Hyaluronic acid was measured by
an enzyme-linked protein binding assay, also on a 96-well
microplate (Corgenix, Westminster, Colo., US). Alpha-2
macroglobulin, apolipoprotein-A1 and haptoglobin were all obtained
by nephelometry (Image, Beckman Coulter, Brea, Calif., US). All
analyses were performed at a central laboratory, PathCentre in
Perth.
[0094] Univariate logistic regression analysis of the variables
tested in the training set revealed age, gender, albumin,
hyaluronic acid, .alpha.-2 macroglobulin and TIMP-1 to be
associated with significant fibrosis (Table 2). TABLE-US-00002
TABLE 2 Association of age, gender and biochemical serum markers
with significant fibrosis in the training cohort (n = 117). Stage
F0/F1 Stage F2-F4 (n = 66) (n = 51) P, univariate Variable Mean
Mean analysis Age, years 38.7 41.9 0.03 Gender (female), % 38.6%
21.7% 0.03 ALT, U/L 123.4 125.3 0.9 GGT, U/L 78.1 111.4 0.1
Bilirubin, .mu.mol/L 10.8 13.0 0.2 Albumin, g/L 42.5 40.4 <0.001
Haptoglobin, g/lL 1.0 0.9 0.4 Hyaluronic Acid, .mu.g/L 20.7 107.3
<0.001 Apolipoprotein A1, g/L 1.7 1.6 0.1 .alpha.-2
macroglobulin, g/L 2.3 3.3 <0.001 TIMP-1, ng/mL 880 1404 0.002
MMP-2, ng/mL 731 830 0.1 Variables presented as n (%) or mean.
[0095] The final predictive model was computed from the results of
the following four biochemical markers; bilirubin, GGT, alpha-2
macroglobulin and hyaluronic acid. The in-house analytical
coefficients of variation were 1.7% at a bilirubin level of 16
.mu.mol/L, 2.7% at a GGT activity of 33 U/L, 2.8% at an alpha-2
macroglobulin level of 2.5 g/L and 3.5% at a hyaluronic acid level
of 50 .mu.g/L.
EXAMPLE 3
[0096] Analysis of Liver Biopsy. Liver biopsies of both training
and validation sets were a minimum of 18 gauge with a minimum of
five portal tracts and were routinely stained with
hematoxylin-eosin and trichrome stains. Biopsies were interpreted
according to the scoring schema developed by the METAVIR group by
two expert liver pathologists who were masked to patient clinical
characteristics and serum measurements. Thirty biopsies were scored
by both pathologists and interobserver agreement was calculated
using Kappa (.kappa.) statistics. Fibrosis was scored on the
5-point METAVIR scale. Necro-inflammatory activity, based on
assessment of piecemeal and lobular necrosis, was graded on a
4-point scale as follows: AO, no activity; A1, mild; A2, moderate;
A3, severe.
EXAMPLE 4
[0097] Statistical Analysis. Using the data from the training set,
associations between each of the ten biochemical markers and the
presence or absence of significant fibrosis were assessed by
logistic regression. In addition, the diagnostic accuracy of each
biochemical marker was assessed using receiver operating
characteristic (ROC) curve analysis. All biochemical markers were
combined with age and gender and entered into stepwise logistic
regression analysis using a forward and a backward elimination
procedure with a significance level of P=0.10. The dependent
variable was defined as significant fibrosis as detected by liver
biopsy. Biochemical markers with a high AUC or a high level of
significance on univariate analysis were added to create different
multivariable models. Models based on different marker
combinations, were then compared using receiver operating
characteristic (ROC) curves to determine which was most accurate in
detecting significant fibrosis. A single model with the fewest
variables and the greatest area under the curve (AUC) was selected
and applied to the validation set. The logistic regression model
consisted of: y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha..sub.2-macroglobul-
in)+(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT))
[0098] with age provided in years; male gender=1, female gender=0,
.alpha..sub.2-macroglobulin in g/L, hyaluronate in .mu.g/L,
bilirubin in .mu.mol/L and GGT in U/L. The Hepascore, H, was
calculated from the following equation: H=y/(1+y).
[0099] Sensitivity, specificity, PPV and NPV for significant
fibrosis, advanced fibrosis and cirrhosis were determined for
various cut-off points between zero and one in the training set and
validation set. The same Hepascore regression model was also used
to calculate the accuracy for determining the combined endpoint of
moderate to severe necroinflammatory activity (A2, A3) versus no or
mild activity (A0, A1). Clinical and demographic characteristics
between the training and validation sets were compared using the
Student's t-test for continuous variables and chi squared test or
Fisher exact test for categorical variables. A P value of less than
0.05 was considered significant. All statistical analysis was done
using Stata version 8 (Stata Corp. 2003. Stata Statistical
Software: Release 8.0. College Station, Tex.: Stata
Corporation).
EXAMPLE 5
[0100] Predictive Model. Biochemical markers assessed in the
training set, were combined with age and gender in logistic
regression analysis to create several models which were predictive
of significant fibrosis. The optimal multivariable model was
considered as having the largest AUC using ROC analysis. This model
(Hepascore) consisted of age, gender, bilirubin, GGT, hyaluronic
acid and .alpha.2 macroglobulin (Table 3) which provided a high AUC
(95% confidence interval, CI) for the prediction of significant
fibrosis (0.852 (95% CI, 0.778-0.926)), as well as for advanced
fibrosis (0.957 (95% CI, 0.918-0.995)) and cirrhosis (0.938 (95%
CI, 0.872-1.000)), as shown in FIG. 1. In comparison, the Fibrotest
results in the training set provided AUC values for significant
fibrosis, advanced fibrosis and cirrhosis of 0.793 (95% CI,
0.706-0.880), 0.906 (95% CI, 0.833-0.979) and 0.966 (95% CI,
0.918-1.000) respectively. TABLE-US-00003 TABLE 3 Multiple logistic
regression model for the prediction of significant fibrosis.
Variable Coefficient SE P Odds ratio (95% CI) Age, years -0.02 0.03
0.44 0.98 (0.92-1.04) Gender, female 0.75 1.13 0.16 2.11
(0.74-6.05) .alpha.-2 macroglobulin, 1.00 0.78 0.0001 2.73
(1.56-4.79) g/L Hyaluronic Acid, 0.03 0.01 0.005 1.03 (1.01-1.05)
.mu.g/L Bilirubin, .mu.mol/L 0.07 0.04 0.09 1.07 (0.99-1.16) GGT,
U/L -0.01 0.01 0.59 1.00 (0.99-1.03)
[0101] The Hepascore (range 0.0-1.0) increased significantly
(P<0.001) as fibrosis stage increased (FIG. 2). A central
cut-off point of 0.5 among the training set, predicted significant
fibrosis (F2 to F4) with a sensitivity of 67% (95% C.I., 58.1-75.2)
and a specificity of 92% (95% C.I., 87.6-97.2). Applying the same
cut-off point of 0.5 for the prediction of advanced fibrosis (F3
and F4), sensitivity was 95% (95% C.I., 91.7-99.2) and specificity
was 81% (95% C.I., 74.0-88.2). When a cut-off point of 0.84 was
applied for detection of cirrhosis (F4), it provided a 71% (95%
C.I., 63.2-79.6) sensitivity and an 84% (95% C.I., 76.9-90.3)
specificity.
EXAMPLE 6
[0102] Model Validation. The four-marker model, plus gender and
age, was applied to the 104 patients in the validation set and
provided AUCs of 0.820 (95% CI, 0.737-0.902) for significant
fibrosis, 0.903 (95% CI, 0.835-0.971) for advanced fibrosis and
0.891 (95% CI, 0.805-0.976) for cirrhosis (FIG. 2).
[0103] Among the validation cohort, 42 of 104 (40%) had a score
.gtoreq.0.5. A cut-off point of 0.5 gave a sensitivity of 63% (95%
CI, 53.4%-72.0%) and a specificity of 89% (95% CI, 82.9%-94.9%) for
the presence of significant fibrosis (F2 to F4). Therefore, 37 of
42 (88%) patients with a score of .gtoreq.0.5 had significant
fibrosis (FIG. 3). A score of <0.5 was observed in the remaining
62 (60%) patients, which excluded advanced fibrosis (F3 and F4)
with a sensitivity of 88% (95% CI, 81.1%-93.9%) and a specificity
of 74% (95% CI, 65.3%-82.2%). A cut-off point of 0.84 yielded a
sensitivity of 71% (95% CI, 61.8%-79.4%) and a specificity of 89%
(95% CI, 82.4-94.6) for predicting cirrhosis (F4).
[0104] The Hepascore accurately predicted different levels of
fibrosis among patients with chronic hepatitis C infection and its
performance was confirmed in an independent validation set of
patients from separate institutions. The Hepascore provided
information for all patients; a score .gtoreq.0.50 was 89-92%
specific for the presence of significant fibrosis (METAVIR
.gtoreq.F2) and a score <0.50 was 88-95% sensitive for the
absence of advanced fibrosis (METAVIR .gtoreq.F3). Thus, in the two
cohorts, a Hepascore .gtoreq.0.50 provided high positive predictive
values for the presence of significant fibrosis of 87% and 88%; a
Hepascore <0.5 provided negative predictive values for advanced
fibrosis of 95% and 98%; and a Hepascore <0.84 provided negative
predictive values for cirrhosis of 94% and 98%.
[0105] The predictive value of a diagnostic test varies according
to the underlying prevalence of the disease or symptom. Therefore,
as treatment is generally recommended when significant fibrosis is
present (Hepatology 39: 1147-71 (2004)), patients with a Hepascore
.gtoreq.0.50 may be considered for anti-viral therapy without the
requirement for liver biopsy. In addition, the exclusion of
advanced fibrosis among patients who have a Hepascore <0.5 may
be particularly useful in providing prognostic information for
patients who are reluctant to undergo biopsy or among elderly
patients who are unlikely to develop liver related morbidity or
mortality in the absence of advanced fibrosis (Lancet 349: 825-32
(1997)). Finally, a score >0.84 is 84%-89% specific for the
presence of cirrhosis. This may be useful to avoid liver biopsy in
patients in whom occult cirrhosis is suspected or to guide
management decisions regarding variceal and cancer screening and
patient follow-up (Gut 49:11-21 (2001)).
[0106] The Hepascore model was accurate in excluding moderate to
severe necro-inflammatory activity (A2 and A3), providing an AUC of
0.707 (95% CI, 0.579-0.835) in the training set, with 59% (95% CI,
50.2%-68.0%) sensitivity and 73% (95% CI, 64.6%-80.7%)
specificity.
EXAMPLE 7
[0107] Prediction of Fibrosis in Patients with
Non-alcoholic/Alcoholic Fatty Liver Disease. In this study,
Hepascore was used for the prediction of liver fibrosis in patients
with non-alcoholic/alcoholic fatty liver disease (NAFLD/AFLD).
Thirteen patients clinically suspected of having NAFLD/AFLD had
liver biopsies, which were graded according to NAFLD activity score
using the scoring system reported by Kleiner et al. (Hepatology
2005; 41: 1313). Serum samples were analysed for hyaluronic acid,
alpha2 macroglobulin, gamma glutamyl transpeptidase and bilirubin.
The intermediate value for each patient was calculated as follows:
y=exp
(-4.185818-(0.0249*age)+(0.7464*gender)+(1.0039*.alpha..sub.2-macroglobul-
in)+(0.0302*hyaluronic acid)+(0.0691*bilirubin)-(0.0012*GGT))
[0108] with age provided in years; male gender=1, female gender=0,
.alpha..sub.2-macroglobulin in g/L, hyaluronate in .mu.g/L,
bilirubin in .mu.mol/L and GGT in U/L. The Hepascore, H, for each
patient was calculated from the following equation: H=y/(1+y).
[0109] The Hepascore was used to predict liver fibrosis in these
patients, wherein a Hepascore greater than or equal to a cut-off
value of 0.5 is indicative of significant fibrosis, and whereas a
Hepascore of less than 0.5 is indicative of an absence of advanced
fibrosis. A Hepascore of greater than or equal to a cut-off value
of 0.84 is indicative of cirrhosis, whereas a Hepascore of less
than a cut-off value of 0.84 is indicative of the absence of
cirrhosis. Case notes were reviewed for the following metabolic
syndrome risk factors: diabetes, elevated body mass index (BMI),
hyperlipidaemia and hypertension. Alcohol consumption was assessed
as standard drinks per week. Liver fibrosis of biopsy samples was
graded using METAVIR score from F0 to F4 with a grade of F2, F3 or
F4 defined as significant fibrosis.
[0110] Ten patients had significant fibrosis on liver biopsy (i.e.,
a METAVIR score of F2-F4) of which three patients had cirrhosis
(i.e., a METAVIR score of F4). Six patients had significant
steatosis (greater than 50% steatosis). Eight patients were
overweight, having a BMI above 25. Two patients had diabetes, five
were hyperlipidaemic, and four were hypertensive. One patient with
morbid obesity had all three risk factors and one patient had two
risk factors (diabetes and hypertension). Six patients had only one
risk factor. Stated alcohol consumption was less than five standard
drinks per week in nine patients, the remaining four patients
consumed more than 21 drinks per week.
[0111] Calculation of Hepascore predicted ten patients with
significant fibrosis and three with insignificant fibrosis. One
patient had a discrepant result: a biopsy grade of F1 compared to a
predicted grade of F2, F3 or F4. Thus, Hepascore correctly
categorized the presence or absence of significant fibrosis in 12
of 13 patients with non-alcoholic/alcoholic fatty liver
disease.
[0112] Unless otherwise defined, all technical and scientific terms
used herein have the same meaning as commonly understood by one of
ordinary skill in the art to which this invention belongs. All
nucleotide sequences provided herein are presented in the 5' to 3'
direction.
[0113] The inventions illustratively described herein may suitably
be practiced in the absence of any element or elements, limitation
or limitations, not specifically disclosed herein. Thus, for
example, the terms "comprising", "including," containing", etc.
shall be read expansively and without limitation. Additionally, the
terms and expressions employed herein have been used as terms of
description and not of limitation, and there is no intention in the
use of such terms and expressions of excluding any equivalents of
the features shown and described or portions thereof, but it is
recognized that various modifications are possible within the scope
of the invention claimed.
[0114] Thus, it should be understood that although the present
invention has been specifically disclosed by preferred embodiments
and optional features, modification, improvement and variation of
the inventions embodied therein herein disclosed may be resorted to
by those skilled in the art, and that such modifications,
improvements and variations are considered to be within the scope
of this invention. The materials, methods, and examples provided
here are representative of preferred embodiments, are exemplary,
and are not intended as limitations on the scope of the
invention.
[0115] The invention has been described broadly and generically
herein. Each of the narrower species and subgeneric groupings
falling within the generic disclosure also form part of the
invention. This includes the generic description of the invention
with a proviso or negative limitation removing any subject matter
from the genus, regardless of whether or not the excised material
is specifically recited herein.
[0116] In addition, where features or aspects of the invention are
described in terms of Markush groups, those skilled in the art will
recognize that the invention is also thereby described in terms of
any individual member or subgroup of members of the Markush
group.
[0117] All publications, patent applications, patents, and other
references mentioned herein are expressly incorporated by reference
in their entirety, to the same extent as if each were incorporated
by reference individually. In case of conflict, the present
specification, including definitions, will control.
[0118] Other embodiments are set forth within the following
claims.
* * * * *